Abstract
In recent years RNA-seq protocols have been developed to investigate a variety of biological problems by measuring the abundance of different RNAs. Many study designs involve performing expensive preliminary studies to screen or optimize experimental conditions. Testing a large number of conditions in parallel may be more cost effective. For example, analyzing tissue/environment-specific gene expression generally implies screening a large number of cellular conditions and samples, without prior knowledge of which conditions are most informative (e.g., some cell types may not respond to certain treatments). To circumvent these challenges, we have established a new two-step high-throughput RNA-seq approach: the first step consists of gene expression screening of a large number of conditions, while the second step focuses on deep sequencing of the most relevant conditions (e.g., largest number of differentially expressed genes). This study design allows for a fast and economical screen in step one, with a more efficient allocation of resources for the deep sequencing of the most biologically relevant libraries in step two. We have applied this approach to study the response to 23 treatments in three lymphoblastoid cell lines demonstrating that it should also be useful for other high-throughput transcriptome profiling applications requiring iterative refinement or screening.
Highlights
We demonstrate this approach by exploring the transcriptional response to a wide panel of environmental perturbations (23 treatments) in three lymphoblastoid cell lines (LCLs) samples
We used a modified RNA-seq protocol better suited for our specific application, but similar results can be achieved with popular commercial RNA-seq kits that allow for high multiplexing (96-well plate format) such as the Illumina TruSeq Stranded mRNA HT Sample preparation kit or the NEBNext Ultradirectional (NEB) library preparation kit
We have shown that shallow sequencing of 96 pooled libraries allows identifying, with minimal costs, the most interesting conditions while capturing biologically relevant and informative gene expression changes
Summary
We investigated whether a shallow sequencing approach can be used as an initial screening step of differential gene expression, to be followed up with deep sequencing of the most informative libraries To this end we have developed a cost-effective two-step strategy that uses the ability to index and pool many (96 or more) RNA-seq libraries in parallel, and it can be used in combination with any RNA-seq technique as long as it allows for multiplexing. This strategy allows the researcher to rapidly screen a large number of sample conditions and strategically allocate sequencing resources for in depth analysis only of the relevant cases. The results show that our approach should be applicable to similar scenarios requiring high throughput screening across multiple cell lines, treatments, time points and/or patient samples in a variety of contexts, such as: population genetic studies, parallel shRNA knockdowns, mutagenesis screens, pharmacological drug testing, stem cell differentiation monitoring and cancer transcriptome profiling
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